Sustainable landfill leachate treatment using refuse and pine bark as a carbon source for biodenitrification

Raw and 10-week composted commercial garden refuse (CGR) materials and pine bark (PB) mulch were evaluated for their potential use as alternative and sustainable sources of carbon for landfill leachate bio-denitrification. Dynamic batch tests using synthetic nitrate solutions of 100, 500 and 2000 mg NO3 L−1 were used to investigate the substrate performance at increasing nitrate concentrations under optimal conditions. Further to this, sequential batch tests using genuine nitrified landfill leachate with a concentration of 2000 mg NO3 L−1 were carried out to evaluate substrates behaviour in the presence of a complex mixture of chemicals present in leachate. Results showed that complete denitrification occurred in all conditions, indicating that raw and composted CGR and PB can be used as sustainable and efficient media for landfill leachate bio-denitrification. Of the three substrates, raw garden refuse yields the fastest denitrification rate followed by 10-week composted CGR and PB. However, the efficiency of the raw CGR was lower when using genuine leachate, indicating the inhibitory effect of components of the leachate on the denitrification process. Ten-week composted CGR performed optimally at low nitrate concentrations, while poor nitrate removal ability was found at higher nitrate concentrations (2000 mg L−1). In contrast, the PB performance was 3.5 times faster than that of the composted garden refuse at higher nitrate concentrations. Further to this, multi-criteria analysis of the process variables provided an easily implementable framework for the use of waste materials as an alternative and sustainable source of carbon for denitrification

Circular closed-loop waste biorefineries: Organic waste as an innovative feedstock for the production of bioplastic in South Africa

The impact of landfills on the environment has come under increasing scrutiny in recent years due to the confounding effects of climate change and water scarcity. There is an urgent need to reduce from landfills the greenhouse gas emissions that cause climate change, and to provide effective treatment solutions for waste, thereby diverting it from landfills. With an estimated 80 million tonnes of plastic waste entering the world’s oceans annually, the accumulation of marine plastic has become a global crisis. Plastic pollution threatens food safety and quality, human health and coastal tourism, and contributes to climate change. For these reasons, there is an urgent need to explore a bioplastic biorefinery process. This review paper examines the potential of organic waste as an alternative carbon source in the efficient and feasible microbial production of polyhydroxyalkanoate (PHA) and polyhydroxybutyrate (PHB), which are precursors for bioplastic. More specifically, this paper presents a concept for a bioplastic biorefinery from a technological perspective, based on data from previous studies. Biofuel production processes are also assessed with the aim of integrating these processes to construct a bioplastic waste biorefinery. Garden refuse and food waste have been shown to be feasible feedstocks for the production of PHAand PHB in singular processes. Diverting these wastes away from landfills will significantly ease the environmental impacts currently associated with their disposal.Significance:• A bioplastic biorefinery is a viable alternative to treat municipal organic waste.• Several biofuel production processes can be integrated into a bioplastic biorefinery system.• Organic waste is poorly managed in South Africa, resulting in greenhouse gas emissions.• Several barriers and considerations must be overcome before implementing the technology at full scale

Long-term emissions from mechanically biologically treated waste: Influence on leachate quality – Part II

Mechanical biological pretreatment of waste prior to disposal is proven to effectively reduce the long-term polluting potentials of landfilled waste. The combined effect of waste pretreatment and flushing, as is possible in landfills operated in tropical or sub-tropical countries, has the potential to further reduce the landfills’ environmental impact. In this study, long-term emissions from pretreated waste were monitored in anaerobic leaching columns operated at increasing liquid-to-solid ratios. The efficiency of the pretreatment, conducted in full-scale passively aerated windrows, was assessed by comparing different treatment periods (8 and 16 weeks). In order to understand the influence of sorting (separated collection) on the pretreatment, the treated waste was sieved in a 50mm diameter sieve and the coarse and fine fractions separately analysed in the leaching columns. The results showed that treating the waste markedly reduces the COD and NH3-N loadings while the coarse fractions show a greater long-term pollutant risk.Keywords: mechanical biological waste treatment, flushing, leaching columns, bioreactor landfill, leachat

Considerations on bio-hydrogen production from organic waste in South African municipalities: A review

Organic waste disposal contributes to 3.8% of GHG emissions to the atmosphere, yet 68.8% of this putrescible waste fraction is still disposed of, untreated, to landfills in South Africa. The implementation of a ban on disposal of organic waste to landfills at provincial level opens up the need to research best technology pathways and waste minimisation strategies to valorise and promote the circularity of diverted waste streams. The SARChI Chair in Waste and Climate Change has developed the WROSE™ (Waste Resource Optimization Scenario Evaluation) model to assist municipalities in selecting the most appropriate waste management solutions. A research gap has been identified in the lack of information on full-scale applications of two-stage anaerobic digestion (2-stage AD) for combined bio-hydrogen and bio-methane production from organic waste. In this review, we explore drivers and barriers to the implementation of 2-stage AD in South Africa and propose possible scenarios using the WROSE™ model for its insertion into an Integrated Waste Management System at municipal level. A literature analysis suggests that 2-stage AD is a potentially viable solution to recover the inherent value of organic waste and promote circularity using bio-hydrogen and bio-methane. However, the currently available organic fraction in the municipal solid waste streams is not a suitable feedstock, as it requires high levels of pre-treatment. Suitable scenarios using the WROSE™ model are proposed for South African municipalities, paving the way for future research towards the scale-up of this technology.Significance:• Organic waste is not managed adequately in South Africa, contributing to greenhouse gas emissions without recovering the intrinsic value of the material.• 2-stage AD is a potentially viable solution to recover the inherent value of organic waste and promote circularity using bio-hydrogen and bio-methane. Several barriers must be overcome before carrying out the technology at full-scale.• A 2-stage AD scenario can be implemented at full-scale into an Integrated Waste Management System using appropriate decision-making tools such as WROSE™

Communication patterns abstractions for programming SDN to optimize high-performance computing applications

Orientador : Luis Carlos Erpen de BonaCoorientadores : Magnos Martinello; Marcos Didonet Del FabroTese (doutorado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 04/09/2017Inclui referências : f. 95-113Resumo: A evolução da computação e das redes permitiu que múltiplos computadores fossem interconectados, agregando seus poderes de processamento para formar uma computação de alto desempenho (HPC). As aplicações que são executadas nesses ambientes processam enormes quantidades de informação, podendo levar várias horas ou até dias para completar suas execuções, motivando pesquisadores de varias áreas computacionais a estudar diferentes maneiras para acelerá-las. Durante o processamento, essas aplicações trocam grandes quantidades de dados entre os computadores, fazendo que a rede se torne um gargalo. A rede era considerada um recurso estático, não permitindo modificações dinâmicas para otimizar seus links ou dispositivos. Porém, as redes definidas por software (SDN) emergiram como um novo paradigma, permitindoa ser reprogramada de acordo com os requisitos dos usuários. SDN já foi usado para otimizar a rede para aplicações HPC específicas mas nenhum trabalho tira proveito dos padrões de comunicação expressos por elas. Então, o principal objetivo desta tese é pesquisar como esses padrões podem ser usados para ajustar a rede, criando novas abstrações para programá-la, visando acelerar as aplicações HPC. Para atingir esse objetivo, nós primeiramente pesquisamos todos os níveis de programabilidade do SDN. Este estudo resultou na nossa primeira contribuição, a criação de uma taxonomia para agrupar as abstrações de alto nível oferecidas pelas linguagens de programação SDN. Em seguida, nós investigamos os padrões de comunicação das aplicações HPC, observando seus comportamentos espaciais e temporais através da análise de suas matrizes de tráfego (TMs). Concluímos que as TMs podem representar as comunicações, além disso, percebemos que as aplicações tendem a transmitir as mesmas quantidades de dados entre os mesmos nós computacionais. A segunda contribuição desta tese é o desenvolvimento de um framework que permite evitar os fatores da rede que podem degradar o desempenho das aplicações, tais como, sobrecarga imposta pela topologia, o desbalanceamento na utilização dos links e problemas introduzidos pela programabilidade do SDN. O framework disponibiliza uma API e mantém uma base de dados de TMs, uma para cada padrão de comunicação, anotadas com restrições de largura de banda e latência. Essas informações são usadas para reprogramar os dispositivos da rede, alocando uniformemente as comunicações nos caminhos da rede. Essa abordagem reduziu o tempo de execução de benchmarks e aplicações reais em até 26.5%. Para evitar que o código da aplicação fosse modificado, como terceira contribuição, desenvolvemos um método para identificar automaticamente os padrões de comunicação. Esse método gera texturas visuais di_erentes para cada TM e, através de técnicas de aprendizagem de máquina (ML), identifica as aplicações que estão usando a rede. Em nossos experimentos, o método conseguiu uma taxa de acerto superior a 98%. Finalmente, nós incorporamos esse método ao framework, criando uma abstração que permite programar a rede sem a necessidade de alterar as aplicações HPC, diminuindo em média 15.8% seus tempos de execução. Palavras-chave: Redes Definidas por Software, Padrões de Comunicação, Aplicações HPC.Abstract: The evolution of computing and networking allowed multiple computers to be interconnected, aggregating their processing powers to form a high-performance computing (HPC). Applications that run in these computational environments process huge amounts of information, taking several hours or even days to complete their executions, motivating researchers from various computational fields to study different ways for accelerating them. During the processing, these applications exchange large amounts of data among the computers, causing the network to become a bottleneck. The network was considered a static resource, not allowing dynamic adjustments for optimizing its links or devices. However, Software-Defined Networking (SDN) emerged as a new paradigm, allowing the network to be reprogrammed according to users' requirements. SDN has already been used to optimize the network for specific HPC applications, but no existing work takes advantage of the communication patterns expressed by those applications. So, the main objective of this thesis is to research how these patterns can be used for tuning the network, creating new abstractions for programming it, aiming to speed up HPC applications. To achieve this goal, we first surveyed all SDN programmability levels. This study resulted in our first contribution, the creation of a taxonomy for grouping the high-level abstractions offered by SDN programming languages. Next, we investigated the communication patterns of HPC applications, observing their spatial and temporal behaviors by analyzing their traffic matrices (TMs). We conclude that TMs can represent the communications, furthermore, we realize that the applications tend to transmit the same amount of data among the same computational nodes. The second contribution of this thesis is the development of a framework for avoiding the network factors that can degrade the performance of applications, such as topology overhead, unbalanced links, and issues introduced by the SDN programmability. The framework provides an API and maintains a database of TMs, one for each communication pattern, annotated with bandwidth and latency constraints. This information is used to reprogram network devices, evenly placing the communications on the network paths. This approach reduced the execution time of benchmarks and real applications up to 26.5%. To prevent the application's source code to be modified, as a third contribution of our work, we developed a method to automatically identify the communication patterns. This method generates different visual textures for each TM and, through machine learning (ML) techniques, identifies the applications using the network. In our experiments the method succeeded with an accuracy rate over 98%. Finally, we incorporate this method into the framework, creating an abstraction that allows programming the network without changing the HPC applications, reducing on average 15.8% their execution times. Keywords: Software-Defined Networking, Communication Patterns, HPC Applications

Self-consistent simulation of quantum shot noise in nanoscale electron devices

An approach for studying shot noise in mesoscopic systems that explicitly includes the Coulomb interaction among electrons, by self-consistently solving the Poisson equation, is presented. As a test, current fluctuations on a standard resonant tunneling diode are simulated in agreement with previous predictions and experimental results. The present approach opens a new path for the simulation of nanoscale electron devices, where pure quantum mechanical and Coulomb blockade phenomena coexist

A multi-wavelength pipeline for pulsar searches

Pulsar studies in the recent years have shown, more than others, to have benefited from a multi-wavelength approach. The INAF - Astronomical Observatory in Cagliari (INAF-OAC) is a growing facility with a young group devoted to pulsar and fast transients studies across the electromagnetic spectrum. Taking advantage of this expertise we have worked to provide a suite of multi-wavelength software and databases for the observations of pulsars and compact Galactic objects at the Sardinia Radio Telescope (SRT). In turn, radio pulsar observations at SRT will be made available, in a processed format, to gamma-ray searches using AGILE and Fermi gamma-ray satellite and, in a near future, they will be complementary to polarimetric X-ray observations with IXPE.Comment: Accepted for publications in Rendiconti Lincei as Proceedings of "A Decade of AGILE: Results, Challenges and Prospects of Gamma-Ray Astrophysics